set_attributes
Arguments
- attributes
a joined table of all attribute metadata
- factors
a table with factor code-definition pairs; see details
- col_classes
optional, list of R column classes ('ordered', 'numeric', 'factor', 'Date', or 'character', case sensitive) will let the function infer missing 'domain' and 'measurementScale' values for attributes column. Should be in same order as attributeNames in the attributes table, or be a named list with names corresponding to attributeNames in the attributes table.
- missingValues
optional, a table with missing value code-deinition pairs; see details
Details
The attributes data frame must use only the recognized column headers shown here. The attributes data frame must contain columns for required metadata. These are:
For all data:
attributeName (required, free text field)
attributeDefinition (required, free text field)
measurementScale (required, "nominal", "ordinal", "ratio", "interval", or "dateTime", case sensitive) but it can be inferred from col_classes.
domain (required, "numericDomain", "textDomain", "enumeratedDomain", or "dateTimeDomain", case sensitive) but it can be inferred from col_classes.
For numeric (ratio or interval) data:
unit (required). Unitless values should use "dimensionless" as the unit.
For character (textDomain) data:
definition (required)
For dateTime data:
formatString (required)
Other optional allowed columns in the attributes table are: source, pattern, precision, numberType, missingValueCode, missingValueCodeExplanation, attributeLabel, storageType, minimum, maximum
The factors data frame, required for attributes in an enumerated domain, must use only the following recognized column headers:
attributeName (required)
code (required)
definition (required)
The missingValues data frame, optional, can be used in the case that multiple missing value codes need to be set for the same attribute. This table must contain the following recognized column headers.
attributeName (required)
code (required)
definition (required)